A wide variety of devices have been developed for non-invasively monitoring physiologic characteristics of patients. For example, an oximetry sensor system may non-invasively detect various patient blood flow characteristics, such as blood-oxygen saturation of hemoglobin in blood, volume of individual blood pulsations supplied to tissue, and/or the rate of blood pulsations corresponding to each heart beat of a patient. During operation, the oximeter sensor emits light and photo-electrically senses the absorption and/or scattering of the light after passage through perfused tissue. A photo-plethysmographic waveform, which corresponds to cyclic attenuation of optical energy through the patient's tissue, may be generated from the detected light. Additionally, one or more physiologic characteristics may be calculated based upon an amount of light absorbed or scattered. More specifically, the light passed through tissue may be selected to be of one or more wavelengths that may be absorbed and/or scattered by the blood in an amount correlative to the amount of the blood constituent present in the blood. The amount of light absorbed and/or scattered may then be used to estimate the amount of blood constituent in tissue using various algorithms.
Many medical devices support multiple output techniques. For example, certain medical devices may output data in a textual format while other medical devices may output data in binary format. Certain medical devices may have different rates of output for the output data.
The automated capture of sensed physiologic values or output data from one or multiple medical devices may lead to improved patient care. However, the act of capturing and displaying the data/information from medical sensors does not necessarily improve care. What may improve care is the ability to present the captured data/information in new ways and to identify cause and effect relationships for such captured data/information.